MANIPULATION
Real-time decentralized neural backstepping controller for a robot manipulator
Ramón García-Hernández, Edgar N. Sánchez, Víctor Santibáñez, Miguel A. Llama, Eduardo Bayro–Corrochano
- Year
- 2009
- Citations
- 2
Abstract
This paper deals with adaptive trajectory tracking for discrete-time MIMO nonlinear systems. A high order neural network (HONN) is used to approximate a decentralized control law designed by the backstepping technique as applied to a block strict feedback form (BSFF). The HONN learning is performed online by an Extended Kalman Filter (EKF) algorithm. The proposed scheme is implemented in real-time to control a two DOF robot manipulator.
Keywords
BacksteppingControl theory (sociology)Computer scienceTrajectoryController (irrigation)Artificial neural networkNonlinear systemExtended Kalman filterKalman filterScheme (mathematics)
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